Counterfeiting of manufactured goods is a worldwide problem, with recent studies estimating that 8% of the world's total GDP is now generated by the manufacturing and sales of counterfeit products. Many classes of counterfeit goods create substantial risks to public health including counterfeit pharmaceutical drugs, auto parts, pesticides, and children's toys. In addition, counterfeit computer chips, aerospace parts, and identification documents present significant risks to national security.
Many different approaches have been tried to uniquely identify and authenticate objects, including serial numbers, bar codes, holographic labels, RFID tags, and hidden patterns using security inks or special fibers. All of these methods can be duplicated, and many add a substantial extra cost to the production of the goods being protected. In addition, physically marking certain objects such as artwork, gemstones, and collector-grade coins can damage or destroy the value of the object.
If identifying or certifying information is stored separately from the object in the form of a label, tag, or certificate the entire identification/certification process must typically be performed again if the object is lost and later recovered, or its chain of control is otherwise compromised. There is a need for solutions that can prove the provenance of an object once the chain of custody is disrupted by the removal of the object from safe custody and/or the loss of the associated identification or certification information.
Other known techniques call for comparing bitmaps of images of the objects themselves, or selected regions of interest. Referring now to FIG. 8, the image of the original object is taken and stored for reference. The whole image is stored, although it may be compressed for efficiency. When a new object is encountered, an image is taken of the new object and directly compared to the original image using XOR or similar algorithms. If there are no (or only statistically insignificant) differences, the images are declared a match and the object is authenticated. Further, FFT or similar transforms may be used to generate a “digital signature” of the image that can be used for comparison. See FIG. 9. However, as in the previous case the same method is used—the resultant bitmapped image is compared with another bitmapped image, and if the pixels match the object is authenticated. Such methods are disclosed in U.S. Pat. No. 7,680,306 to Boutant et al. Bitmapped techniques are inefficient due to issues like file size, and have serious limitations that make them effectively unusable in most real world applications, due to variable lighting and orientation of the images, and the authentication of worn, damaged or otherwise altered objects.